Next Challenges in Optical Networking Research:
Contribution from the CaON cluster
Dimitra Simeonidou: dsimeo@essex.ac.uk, Sergi Figuerola: sergi.figuerola@i2cat.net
The CaON Vision of Future Optical Networks
 Application driven and technology enabled
High-speed data
400G, 1Tb/s
Residential
Media
Cloud
Application Driven
Intelligent
Adaptive
Optical
Networks
Flexible
Network
Flexible use of technology
Elastic use of resources
MULTI-BAND
SSS
MULTI-BAND
AMPLIFIER
Technology Enabled
FAST OPTICAL
SWITCH
SDM
(DE)MUX
MULTI-BAND
SSS
BROADBAND
λ-CONVERSION
The CaON Reference model I
 CaON reference model presents a layered architecture linking optical
networks with future services and applications
Cloud/Service Layer
(e.g. app middleware layer)
Network Control Plane Layer
(i.e. network provisioning layer)
Physical Infrastructure(s*)
SLA Layer
Application Layer
(i.e. final consumers)
Virtualisation Layer
* = (s) to reflect network & IT and multiplicity of infrastructures
Management Layer(s)
 The model promotes the convergence of the optical infrastructure
layers with upper layers and aims to strategically position optical
networks as key enabler of Future Internet and cloud networking
service deployment
The CaON Reference model II
 A bottom-up reference model, where the infrastructure and provisioning
layers, together with cross-layer SLA and the management, are
identified the key focus for future research trends within the CaON
cluster community.
Cloud/Service Layer
(e.g. app middleware layer)
Network Control Plane Layer
(i.e. network provisioning layer)
Physical Infrastructure(s*)
SLA Layer
Application Layer
(i.e. final consumers)
Virtualisation Layer
* = (s) to reflect network & IT and multiplicity of infrastructures
Management Layer(s)
 The physical infrastructure layer covers from the core to the access
optical network technologies.
Key Research Challenges for Realizing the CaON
Reference Model
– Support for Multi-gigabit Access Rates (FP7 ALPHA, OASIS)
– Spectrum management: Flexible, Elastic Optical Layer (FP7
STRONGEST, FP7 call 8 IDEALIST)
• Architectures on Demand
– Control Plane (FP7 MAINS and STRONGEST)
• Targeted extensions for dynamic and data plane-aware network services
– Software/Hardware Defined Network Programmability (FIRE OFELIA
and FIRE call 8 ALIEN)
• For infrastructure and service adaptation
– Optical Network and IT Convergence (FP7 GEYSERS)
• Infrastructure Virtualisation, Slicing and Isolation
– Optical Network Cognition (FP7 CHRON, UK EPSRC Photonics
HyperHighway)
– Energy Efficient Optical Networks (FP7 STRONGEST and TRENT)
Spectrum Management: Elastic Resource Allocation
 Flexible allocation of resources in time and frequency in order to:
– Accommodate applications with arbitrary requirements
Video conference/Virtual Presence
High-speed data transmission 400G, 1T
Gaming
Education/Remote Learning
Elastic Time and Frequency plus Space Allocation
 Elastic frequency allocation to enable:
– Support for high-speed channels with arbitrary bandwidth requirements
– Better spectral efficiency for lower bit rates
 Elastic time allocation for:
Space
– Efficient all-optical switching of sub-wavelength traffic
– Finer all-optical bandwidth granularities
Novel
Fibres and
Fibre-based
components
Continuous channels
at various bit-rates
time
λ
User traffic at various
bit-rates and
modulation formats
Optical Networks on Demand
 Adapt to traffic profile
 Support arbitrary switching-granularity
 Dynamic Infrastructure Composition (including VI)
 Dynamic architecture reconfiguration
 Modular infrastructure planning
 Seamless integration with other technology domains (network + IT)
 Hitless upgrade with new functionality
– Wavelength conversion
– Regeneration
– Optical signal processing
– Space division multiplexing (multi-core, multimode)
– Quantum technologies
– Other?
Support of Multi-Gbps Access Rates:
 Acceleration of access deployment through
– Reduced total cost of ownership
– Converged solutions supporting transport of mobile and fixed traffic in both
front- and backhaul scenarios
 Seamless integration of access and metro/aggregation
– Unified control and management planes
– Virtualization and context-aware networking
 New solutions for simultaneous:
– More users per feeder (>1000)
– Higher speeds (up to 10 Gb/s peak)
– longer reach (100 km)
 Green and fast (1 Gb/s and beyond) home networking
Optical network control plane:
 Main research challenges include
– True multi-vendor and multi-carrier control plane solutions, including
extensions for elastic technologies
– Split architectures that decouple the control plane from the optical
transport
• OpenFlow as an open/vendor-independent interface to network data plane
• Multi-technology and multi-domain path computation services coupled with
traffic optimization
• Software Defined Networking at large
– Control plane interfaces to external end-user “systems” (e.g. clouds) for
any type of bandwidth-on-demand service and seamless integration
with the service layer workflows.
Optical Network and IT Convergence: for High
Performance, Global Reach Clouds
 Provisioning over hybrid infrastructures composed of both IT
resources (i.e. compute, storage, data centres) and optical
networks
 It will require :
– Virtualise the physical optical network infrastructure (analogue or
digital)
– Federate heterogeneous resources from different providers
– Unified management and provisioning procedures for the whole
integration with the IT network infrastructures
Specific Issues in Optical Network Virtualization
 Optical networks are analogue in nature
– More complexity than L2/L3 (digital domain) virtualization as a result of physical layer
impairments and constraints
– Slice isolation is a big challenge in optical networks
 Physical layer impairments
– Affect the isolation between VIs
– Newly composed VIs will affect the existing ones
– Affect the ultimate feasibility of VIs
 Wavelength continuity constraint
– Affect the network resource utilization
 Can we use new infrastructure capabilities such as Space Division Multiplexing (multicore?)
Cognitive, self managed optical networks:
 Dynamically re-purpose, evolve, self-adapt and self-optimize
functions/devices/systems of the optical network.
– Optical/opto-electronic technologies that would allow for environment-aware
systems that can change any parameter based on interaction with the
environment with or without user assistance
– Cognitive control and management plane for dynamic infrastructure selfadaptation across heterogeneous systems.
Energy efficient optical networking:
 Improve the design, planning and operations for energy aware
management capable of 100 times energy consumption reduction
– Introduction of new simpler protocols
– Definition of energy friendly resilience
– Support of planning and routing algorithms
 Focus on energy efficient optical network services for applications such as
P2P, grid or cloud services